Your comment will probably end up buried, but it does raise the question - if they want more female employees, was the issue in the training data, or their recruitment process?
This should be obvious when testing. Whether the algorithm discriminates should be a top priority for designing these algorithms. That's half the damn math of machine learning. If you can construct an AI, you should know how to test it for flaw in reasoning. It's just another layer of ML to do that. Outliers. It's short sighted to push these things out assuming their output is correct just because it looks 'normal'.
This should be obvious when testing. Whether the algorithm discriminates should be a top priority for designing these algorithms. That's half the damn math of machine learning. If you can construct an AI, you should know how to test it for flaw in reasoning. It's just another layer of ML to do that. Outliers. It's short sighted to push these things out assuming their output is correct just because it looks 'normal'.